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Marcos Carlomagno MCarlomagno

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Building @OpenZeppelin ⚡️

MCarlomagno / tensorflow-service.dart

Created September 5, 2020 14:55

	await Tflite.loadModel(
	model: "assets/mobilenet_v1_1.0_224.tflite",
	labels: "assets/labels.txt",
	);

MCarlomagno / recognitions.dart

Last active September 5, 2020 16:14

	_cameraController.startImageStream((img) async {
	List<dynamic> recognitions = await Tflite.runModelOnFrame(
	bytesList: img.planes.map((plane) {
	return plane.bytes;
	}).toList(), // transforms the image into a bit array
	imageHeight: img.height,
	imageWidth: img.width,
	numResults: 3,
	);
	print(recognitions); // shows the predictions in console

MCarlomagno / recognition-structure.dart

Last active September 5, 2020 16:13

MCarlomagno / performance.dart

Created September 5, 2020 15:08

	_cameraController.startImageStream((img) async {
	if (available) {
	available = false;
	await _tensorflowService.runModel(img); // Tflite.runModelOnFrame(...) code
	await Future.delayed(Duration(seconds: 1));
	available = true;
	}
	});

MCarlomagno / index.html

Created September 11, 2020 01:54

MCarlomagno / index.js

Created September 11, 2020 01:55

	import * as toxicity from '@tensorflow-models/toxicity';
	...

MCarlomagno / index.js

Created September 11, 2020 02:02

	let model;

	...

	const startUp = async () => {
	...

	// Loads the model with threshold = 0.7 and labels = ['toxicity']
	// labels can also include any of this range of values:
	// ['identity_attack', 'insult', 'obscene', 'severe_toxicity', 'sexual_explicit', 'threat', 'toxicity']

MCarlomagno / index.js

Created September 11, 2020 02:07

	const fetchTweets = async (text) => {

	// fetch tweets from server
	// enviroment [string]: Base url to the express.js server app
	// text [string]: username of the tweets author
	// tweetsToSearch [number]: number of tweets (10, 20, 50 or 100)
	const result = await fetch(`${enviroment}/twits/${text}/${tweetsToSearch}`);
	const response = await result.json();

	return response.body;

MCarlomagno / index.js

Created September 11, 2020 02:13


	const classify = (inputs) => {
	// model previously loaded
	const results = await model.classify(inputs);
	return inputs.map((d, i) => {
	const obj = {'text': d};
	results.forEach((classification) => {
	obj[classification.label] = classification.results[i].match;
	});
	return obj;

MCarlomagno / index.js

Created September 11, 2020 02:14

	const showResults = (predictions) => {
	let found = false;

	predictions.map((p) => {
	if(p.toxicity !== false) {
	found = true;
	var results = document.getElementById("results");
	var element = document.createElement('p');
	element.textContent = p.text;
	results.appendChild(element);